Mês Abordagem infrações CNH apreendida
1 2017-01-01 3138 328 303
2 2017-02-01 4898 644 592
3 2017-03-01 3597 431 414
4 2017-04-01 3760 489 458
5 2017-05-01 2843 375 369
6 2017-06-01 3888 526 498
7 2017-07-01 3187 335 320
8 2017-08-01 3294 342 342
9 2017-09-01 3027 383 348
10 2017-10-01 3496 444 420
11 2017-11-01 3844 419 399
12 2017-12-01 3369 411 394
13 2018-01-01 4029 403 387
14 2018-02-01 5557 648 599
15 2018-03-01 4548 322 317
16 2018-04-01 4155 388 357
17 2018-05-01 4119 250 243
18 2018-06-01 3126 438 399
19 2018-07-01 4513 449 431
20 2018-08-01 4294 484 454
21 2018-09-01 4021 333 298
22 2018-10-01 3253 361 341
23 2018-11-01 4750 374 353
24 2018-12-01 3080 282 254
25 2019-01-01 4380 418 378
26 2019-02-01 5019 512 463
27 2019-03-01 5902 602 532
28 2019-04-01 5197 480 481
29 2019-05-01 6161 544 498
30 2019-06-01 4766 517 464
31 2019-07-01 6020 525 489
32 2019-08-01 6519 493 464
33 2019-09-01 5635 495 460
34 2019-10-01 3977 383 355
35 2019-11-01 6773 606 541
36 2019-12-01 5762 488 430---
title: "Dashboard sobre a Lei Seca - Salvador/BA"
author: "William Sacramento"
output:
flexdashboard::flex_dashboard:
orientation: columns
theme: cerulean
logo: logo4.png
social: menu
source_code: embed
navbar:
- { title: "Sobre mim", href: "https://linkedin.com/in/william-sacramento-a9605a219" }
---
```{r setup, include=FALSE}
library(rbokeh)
library(flexdashboard)
library(readxl)
dados <- read_excel("C:/UFBa/Projeto/dbleiseca/data/lei_seca.xlsx")
```
# Visualização {data-icon="fa-signal"}
## Column {.sidebar}
Dashboard inicial para apresentar os dados referentes a Lei Seca na cidade de Salvador-Bahia.
Fonte dos dados: Transalvador
## Column {data-width=600}
### Abordagem
```{r}
library(ggplot2)
library(babynames)
library(dplyr)
# Plot
g <- ggplot(dados, aes(Mês, Abordagem))+
geom_line(colour = 'green')
g
```
## Column {data-width=400}
### Infrações
```{r}
library(ggplot2)
library(babynames)
library(dplyr)
# Plot
g <- ggplot(dados, aes(Mês, infrações))+
geom_line(colour = 'red')
g
```
### CNH Apreendida
```{r}
library(ggplot2)
library(babynames)
library(dplyr)
# Plot
g <- ggplot(dados, aes(Mês, `CNH apreendida`))+
geom_line(colour = 'blue')
g
```
# Tabela {data-icon="fa-table"}
### Tabela
```{r}
dados1 <- as.data.frame(dados)
dados1
```